Publication Analysis of (E-)Tourism

Publication Analysis of (E-)Tourism

Tomas Cahlik (Charles University Prague, Czech Republic & University of Economics Prague, Czech Republic) and Elena Kuchina (University of Economics Prague, Czech Republic)
Copyright: © 2015 |Pages: 19
DOI: 10.4018/978-1-4666-8577-2.ch001
OnDemand PDF Download:
$30.00
List Price: $37.50

Abstract

This chapter presents how e-tourism mirrors in three scientific databases: the Web of Knowledge, Scopus and Google Scholar. Based on the data from these databases, two research questions are answered: How is the number of scientific papers on e-tourism going to develop in the future? What is the probable scenario for future tourism development? We estimate a logistic model for the number of scientific papers in all three databases. Our main finding concerning the first question is that e-tourism as a scientific field is behind its zenith already. Our main finding concerning the second question is that e-tourism supports transition from organized to individual tourism. For answering the third research question “Is there a link between the number of publications on tourism and economic indicators on tourism?” we use numbers of publications from the Factiva database and economic indicators on tourism from the World Bank web page. Using the CCEMG estimator for panel data we find that statistically important links surely exist, even if the interpretation is sometimes not clear. This finding opens opportunities for subsequent research.
Chapter Preview
Top

Introduction

Information and Communication Technologies (ICTs) have penetrated all human activities in the last 20 years. They have offered a lot of challenges and opportunities to tourism as well. As e-governance has been developed with governance, e-tourism has been developed with tourism. This development has been mirrored in scientific research and is documented in scientific databases. The picture changes in time, so it is important to stress that all data we work with are from April 2014.

In the Web of Knowledge (WoK) database, there are 112 documents found with search e-tourism. Before 2007, yearly production had never been above 10, since that time it slightly fluctuates around 15 documents per year. Scopus database gives a similar picture: 210 documents altogether, before 2005 never above 10 documents per year, since that time fluctuations around 30 documents per year. Google Scholar, being asked about e-tourism, answers above 5000 items, before 2000 never above 100 items per year, since 2010 fluctuations around 600 items yearly. The content of all documents defines the scientific field e-tourism; this field is surely subfield of tourism, but has also strong links with other scientific fields, e.g. computer science.

Interesting data and information can be found with deeper analysis of the scientific field e-tourism. Two methods are used for getting and summarizing the information from the documents´ databases: Reading of abstracts and of the full text of most influential or most relevant documents and verbal description of established or emerging themes is the first one. Using analytical instruments built into the databases is the second - very efficient - one. These instruments allow analyzing production of articles in time and in space - according to countries, authors, affiliations of the authors, document types and subject areas.

Data and information found with the use of methods mentioned above are used in this chapter in two ways: for prediction of the number of articles on e-tourism in all three databases in the next years - our first research question - and for specification of one possible scenario of future development of tourism - our second research question.

For predicting the number of articles we assume that it follows a logistic model and we estimate this model both for e-tourism and tourism in all three databases. We get acceptable estimates for e-tourism in the WoK and Google Scholar and for tourism in the WoK and Scopus. Stylized interpretation of our results is that e-tourism as a scientific field is behind its zenith already. Explanation could be that until now e-tourism has been the best suited field for examining different themes related to business-to-business (B2B) research. With maturation of other application fields the B2B research will get more hints from those other fields and e-tourism loses its “monopolistic” position.

Specification of probable scenario of future development of tourism is based on the main stylized fact obtained from the content analysis of e-tourism documents in scientific databases. This stylized fact can be formulated as: E-tourism supports transition from organized to individual tourism. The strength of this formulation is that it does not contradict the common sense. We present a model of the current state of the tourism network, discuss shortly how innovations on tourism occur and specify the model of tourism network of the future we consider to be probable. As an illustration, we use development of tourism in the Czech Republic – our home country.

Our third research question concerns the link between the number of publications and economic indicators on tourism. The basic technical problem here is the small number of e-tourism publications in the WoK and Scopus databases. That is why we need some supporting information from a bigger database. Google Scholars is surely big, but the searching tools in this database give approximate results only. Therefore we decided to count documents on e-tourism and tourism in the Factiva database. Factiva aggregates information more relevant to business than to science; from newspapers, journals, magazines, television and radio transcripts etc. Saying differently we have abstained from analyzing the link between the number of scientific publications and economic indicators on tourism – because of technical reasons. We use “International Tourist Arrivals”, “Tourism Receipts” and “International Tourism Expenditures” from the World Bank web page as economic indicators on tourism. Using the CCEMG estimator for panel data we find that statistically important links surely exist, even if the interpretation is sometimes not clear. This finding opens opportunities for subsequent research.

The aim of this chapter is:

Complete Chapter List

Search this Book:
Reset